Endian Lin — accepted AI-conference papers

2026

PEOD: A Pixel-Aligned Event-RGB Benchmark for Object Detection Under Challenging Conditions

Luoping Cui, Hanqing Liu, Mingjie Liu, Endian Lin, Donghong Jiang, Yuhao Wang +1

AAAI 2026technical

Robust object detection for challenging scenarios increasingly relies on event cameras, yet existing Event-RGB datasets remain constrained by sparse coverage of extreme conditions and low spatial resolution (≤ 640 × 480), which prevents comprehensive evaluation of detectors under challenging scenari

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2026

RE-VLM: Event-Augmented Vision-Language Model for Scene Understanding

Hanqing Liu, Mingjie Liu, Luoping Cui, Endian Lin, Donghong Jiang, Chuang Zhu

CVPR 2026

Conventional vision-language models (VLMs) struggle to interpret scenes captured under adverse conditions (e.g., low light, high dynamic range, or fast motion) because standard RGB images degrade in such environments. Event cameras provide a complementary modality: they asynchronously record per-pix

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